Document type : news item from site Arla Foods
Preview: Dairy cooperative, Arla Foods, has been working with animal behavioural science and technology partners FAI Farms, Nedap and Alta Genetics to determine how, exactly, to measure the happiness of a cow. The project is being driven with the knowledge that the wellbeing of herds is determined by how they are managed within a given environment, rather than which type of production system the farm operates. The cumulative data is helping Arla and the wider dairy industry create a 'happy cow measure', which, for the first time in industry history, looks to automate the measurement of mental wellbeing for cows.
The project is being led by the Arla UK 360 Programme, an initiative supported by Aldi and Morrisons and developed by Arla's UK farmers, with the aim of making practices more sustainable, responsible and efficient. The Happy Cow project is being spearheaded at the Arla UK 360 Innovation Farm based near Aylesbury, where the herd are using Nedap sensor technology capable of tracking activity, behaviour and location. Sustainability experts at FAI Farms are now analysing data to identify key behavioural traits that signal changes positive welfare.
With many farmers across the UK already using technology to monitor and manage heat detection and early signs of illness, the potential to identify further uses for this data and technology investment is huge. The Happy Cow project is working to show that the data already being captured on farm in wearable technology can be further interrogated to monitor cow behaviour and mental wellbeing, something that until now, has always been a 'feeling' rather than a tangible measure for the industry to monitor.
FAI Farms began reviewing reports and analyses on what key behaviours can be measured, this was then tested by an animal behavioural scientist observing the cows at the Arla UK 360 Innovation Farm to verify and define key positive behavioural indicators which are demonstrated by individual cow and herd interactions. These key positive behaviour indicators included social grooming, synchronicity and brush use, which ordinarily would not be monitored and never before automatically measured. While this set the benchmark for monitoring, the study also set out to see how these principles could be automated, to eventually pave the way for a scaled-up system.